Abstract
Artificial Intelligence (AI) is reshaping the healthcare landscape by enhancing early disease detection and improving diagnostic accuracy. By leveraging machine learning and deep learning techniques, AI can process vast amounts of medical data, identify patterns, and assist clinicians in making faster, more accurate diagnoses. This paper examines the role of AI in medical diagnostics, with a focus on early detection of chronic diseases, such as cancer and cardiovascular conditions, through case studies. It also highlights the challenges, including data privacy concerns, algorithmic bias, and the need for regulatory frameworks to ensure safe AI implementation. Despite these hurdles, AI-powered diagnostics hold the potential to revolutionize healthcare by reducing costs, improving patient outcomes, and advancing personalized medicine. Keywords: Artificial Intelligence (AI), Early Disease Detection, AI Diagnostics, Machine Learning, Deep Learning.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Research Output Journal of Biological and Applied Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
